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discover_music

Use natural language queries to discover music from your library and get smart recommendations based on your taste.

Instructions

Natural language music discovery with smart recommendations based on your preferences and library

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language query (e.g., 'songs from the 90s', 'rock bands I haven't heard', 'something like Modest Mouse')
contextNoAdditional context for the search (optional)
limitNoMaximum number of results to return (default: 10)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, and description fails to disclose behavioral traits such as whether the tool is read-only, authentication requirements, or rate limits. The description only gives a high-level promise of smart recommendations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence that efficiently conveys core purpose without fluff. Could be slightly more structured but overall concise.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Lacks critical details about return format, pagination, error handling, and how recommendations work. Without annotations or output schema, the description should provide more context for an agent to use it effectively.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

All three parameters have descriptions in the schema, and the tool description adds no significant additional meaning beyond framing the query as personalized. Baseline 3 due to high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states it's for natural language music discovery with recommendations, distinguishing it from exact search siblings like search_plex. However, it does not explicitly contrast with siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies usage for exploratory or preference-based queries, but lacks explicit when-to-use or when-to-avoid guidance compared to siblings like search_plex or browse_collection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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